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Displaying similar documents to “Absolute minimizer in convex programming by exponential penalty.”

Solving convex program via Lagrangian decomposition

Matthias Knobloch (2004)

Kybernetika

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We consider general convex large-scale optimization problems in finite dimensions. Under usual assumptions concerning the structure of the constraint functions, the considered problems are suitable for decomposition approaches. Lagrangian-dual problems are formulated and solved by applying a well-known cutting-plane method of level-type. The proposed method is capable to handle infinite function values. Therefore it is no longer necessary to demand the feasible set with respect to the...

LFS functions in multi-objective programming

Luka Neralić, Sanjo Zlobec (1996)

Applications of Mathematics

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We find conditions, in multi-objective convex programming with nonsmooth functions, when the sets of efficient (Pareto) and properly efficient solutions coincide. This occurs, in particular, when all functions have locally flat surfaces (LFS). In the absence of the LFS property the two sets are generally different and the characterizations of efficient solutions assume an asymptotic form for problems with three or more variables. The results are applied to a problem in highway construction,...

Convergence of optimal strategies under proportional transaction costs

Rafał Kucharski (2008)

Banach Center Publications

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A discrete-time financial market model with finite time horizon and transaction costs is considered, with a sequence of investors whose preferences are described by a convergent sequence of strictly increasing and strictly concave utility functions. Proportional costs are approximated by strictly convex costs. Existence of the optimal consumption-investment strategies is obtained, as well as convergence of the value functions and convergence of subsequences of optimal strategies. ...